DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation

Nasopharyngeal Carcinoma segmentation in magnetic resonance imagery (MRI) is vital to radiotherapy. Exact dose delivery hinges on an accurate delineation of the gross tumor volume (GTV). However, the large-scale variation in tumor volume is intractable, and the performance of current models is mostl...

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Bibliographic Details

Published in:	Sensors (Basel, Switzerland) Vol. 21; no. 23; p. 7877
Main Authors:	Li, Yang, Han, Guanghui, Liu, Xiujian
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 26.11.2021 MDPI
Subjects:	Cancer Datasets Deep learning DenseNet Machine learning nasopharyngeal carcinoma segmentation Radiation therapy Semantics supervised learning Support vector machines Throat cancer Tumors
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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